Shaoshu Su is a Ph.D. student at the Department of Computer Science and Engineering (CSE), University at Buffalo (UB). His research interests include Learning-based Visual Odometry, Reinforcement Learning, as well as Planning and Control problems in Robotics 🤖.

Experience

Research Scientist
- University at Buffalo (UB), USA
- Nov. 2022 - Sept. 2023
Visiting Student
- University of California, Berkeley, USA
- Mar. 2022 - Nov. 2022
Research Assistant
- University of California, Riverside, USA
- 2020 - 2022

Education

Ph.D. in Computer Science
- University at Buffalo (UB), USA
- 2023 - Present
Master of Science in Electrical Engineering
- University of California, Riverside, USA
- Sep. 2019 - Mar. 2022
Bachelor of Science in Aerospace Engineering
- Beijing Institute of Technology, Beijing, China
- Sep. 2015 - June 2019

Emails

Personal Email: shaoshus@sairlab.org
School Email: shaoshus@buffalo.edu

Publications

Imperative Learning: A Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy.
Chen Wang, Kaiyi Ji, Junyi Geng, Zhongqiang Ren, Taimeng Fu, Fan Yang, Yifan Guo, Haonan He, Xiangyu Chen, Zitong Zhan, Qiwei Du, Shaoshu Su, Bowen Li, Yuheng Qiu, Yi Du, Qihang Li, Yifan Yang, Xiao Lin, Zhipeng Zhao.
arXiv preprint arXiv:2406.16087, 2024.

SAIR Lab Recommended
```
@article{wang2024imperative,
  title = {Imperative Learning: A Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy},
  author = {Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng},
  journal = {arXiv preprint arXiv:2406.16087},
  year = {2024},
  url = {https://arxiv.org/abs/2406.16087},
  code = {https://github.com/sair-lab/iSeries},
  website = {https://sairlab.org/iseries},
  addendum = {SAIR Lab Recommended}
}
```
```
Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng, "Imperative Learning: A Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy," arXiv preprint arXiv:2406.16087, 2024.
```
iSLAM: Imperative SLAM.
Taimeng Fu, Shaoshu Su, Yiren Lu, Chen Wang.
IEEE Robotics and Automation Letters (RA-L), 2024.

SAIR Lab Recommended
```
@article{fu2024islam,
  title = {{iSLAM}: Imperative {SLAM}},
  author = {Fu, Taimeng and Su, Shaoshu and Lu, Yiren and Wang, Chen},
  journal = {IEEE Robotics and Automation Letters (RA-L)},
  year = {2024},
  url = {https://arxiv.org/abs/2306.07894},
  code = {https://github.com/sair-lab/iSLAM/},
  video = {https://youtu.be/rtCvx0XCRno},
  website = {https://sairlab.org/iSLAM},
  addendum = {SAIR Lab Recommended}
}
```
```
Fu, Taimeng and Su, Shaoshu and Lu, Yiren and Wang, Chen, "iSLAM: Imperative SLAM," IEEE Robotics and Automation Letters (RA-L), 2024.
```
SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments.
Shibo Zhao, Yuanjun Gao, Tianhao Wu, Damanpreet Singh, Rushan Jiang, Haoxiang Sun, Mansi Sarawata, Warren C Whittaker, Ian Higgins, Shaoshu Su, Yi Du, Can Xu, John Keller, Jay Karhade, Lucas Nogueira, Sourojit Saha, Yuheng Qiu, Ji Zhang, Wenshan Wang, Chen Wang, Sebastian Scherer.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
```
@inproceedings{zhao2024subt,
  title = {{SubT-MRS} Dataset: Pushing SLAM Towards All-weather Environments},
  author = {Zhao, Shibo and Gao, Yuanjun and Wu, Tianhao and Singh, Damanpreet and Jiang, Rushan and Sun, Haoxiang and Sarawata, Mansi and Whittaker, Warren C and Higgins, Ian and Su, Shaoshu and Du, Yi and Xu, Can and Keller, John and Karhade, Jay and Nogueira, Lucas and Saha, Sourojit and Qiu, Yuheng and Zhang, Ji and Wang, Wenshan and Wang, Chen and Scherer, Sebastian},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://arxiv.org/abs/2307.07607},
  video = {https://youtu.be/mkN72Lv8S7A},
  website = {https://sairlab.org/datasets/subtmrs}
}
```
```
Zhao, Shibo and Gao, Yuanjun and Wu, Tianhao and Singh, Damanpreet and Jiang, Rushan and Sun, Haoxiang and Sarawata, Mansi and Whittaker, Warren C and Higgins, Ian and Su, Shaoshu and Du, Yi and Xu, Can and Keller, John and Karhade, Jay and Nogueira, Lucas and Saha, Sourojit and Qiu, Yuheng and Zhang, Ji and Wang, Wenshan and Wang, Chen and Scherer, Sebastian, "SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
```
PyPose v0.6: The Imperative Programming Interface for Robotics.
Zitong Zhan, Xiangfu Li, Qihang Li, Haonan He, Abhinav Pandey, Haitao Xiao, Yangmengfei Xu, Xiangyu Chen, Kuan Xu, Kun Cao, Zhipeng Zhao, Zihan Wang, Huan Xu, Zihang Fang, Yutian Chen, Wentao Wang, Xu Fang, Yi Du, Tianhao Wu, Xiao Lin, Yuheng Qiu, Fan Yang, Jingnan Shi, Shaoshu Su, Yiren Lu, Taimeng Fu, Karthik Dantu, Jiajun Wu, Lihua Xie, Marco Hutter, Luca Carlone, Sebastian Scherer, Daning Huang, Yaoyu Hu, Junyi Geng, Chen Wang.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, 2023.
```
@inproceedings{zhan2023pypose,
  title = {{PyPose} v0.6: The Imperative Programming Interface for Robotics},
  author = {Zhan, Zitong and Li, Xiangfu and Li, Qihang and He, Haonan and Pandey, Abhinav and Xiao, Haitao and Xu, Yangmengfei and Chen, Xiangyu and Xu, Kuan and Cao, Kun and Zhao, Zhipeng and Wang, Zihan and Xu, Huan and Fang, Zihang and Chen, Yutian and Wang, Wentao and Fang, Xu and Du, Yi and Wu, Tianhao and Lin, Xiao and Qiu, Yuheng and Yang, Fan and Shi, Jingnan and Su, Shaoshu and Lu, Yiren and Fu, Taimeng and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Hutter, Marco and Carlone, Luca and Scherer, Sebastian and Huang, Daning and Hu, Yaoyu and Geng, Junyi and Wang, Chen},
  year = {2023},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop},
  url = {https://arxiv.org/abs/2309.13035},
  code = {https://github.com/pypose/pypose},
  video = {https://youtu.be/XDtUDIWuGng},
  website = {https://sairlab.org/pypose/}
}
```
```
Zhan, Zitong and Li, Xiangfu and Li, Qihang and He, Haonan and Pandey, Abhinav and Xiao, Haitao and Xu, Yangmengfei and Chen, Xiangyu and Xu, Kuan and Cao, Kun and Zhao, Zhipeng and Wang, Zihan and Xu, Huan and Fang, Zihang and Chen, Yutian and Wang, Wentao and Fang, Xu and Du, Yi and Wu, Tianhao and Lin, Xiao and Qiu, Yuheng and Yang, Fan and Shi, Jingnan and Su, Shaoshu and Lu, Yiren and Fu, Taimeng and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Hutter, Marco and Carlone, Luca and Scherer, Sebastian and Huang, Daning and Hu, Yaoyu and Geng, Junyi and Wang, Chen, "PyPose v0.6: The Imperative Programming Interface for Robotics," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, 2023.
```
Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing.
Shaoshu Su, Ce Hao, Catherine Weaver, Chen Tang, Wei Zhan, Masayoshi Tomizuka.
22nd IFAC World Congress vol. 56, no. 2, pp. 7940–7947, 2023.
```
@inproceedings{su2023double,
  title = {Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing},
  author = {Su, Shaoshu and Hao, Ce and Weaver, Catherine and Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi},
  booktitle = {22nd IFAC World Congress},
  volume = {56},
  number = {2},
  pages = {7940--7947},
  year = {2023},
  publisher = {Elsevier},
  url = {https://www.sciencedirect.com/science/article/pii/S2405896323006936}
}
```
```
Su, Shaoshu and Hao, Ce and Weaver, Catherine and Tang, Chen and Zhan, Wei and Tomizuka, Masayoshi, "Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing," 22nd IFAC World Congress, 2023.
```
Multirobot Fully Distributed Active Joint Localization and Target Tracking.
Shaoshu Su, Pengxiang Zhu, Wei Ren.
IEEE Transactions on Control Systems Technology, 2023.
```
@article{su2023multirobot,
  title = {Multirobot Fully Distributed Active Joint Localization and Target Tracking},
  author = {Su, Shaoshu and Zhu, Pengxiang and Ren, Wei},
  journal = {IEEE Transactions on Control Systems Technology},
  year = {2023},
  publisher = {IEEE},
  url = {https://ieeexplore.ieee.org/abstract/document/10093944}
}
```
```
Su, Shaoshu and Zhu, Pengxiang and Ren, Wei, "Multirobot Fully Distributed Active Joint Localization and Target Tracking," IEEE Transactions on Control Systems Technology, 2023.
```
An optimization approach to fully distributed active joint localization and target tracking in multi-robot systems.
Shaoshu Su, Pengxiang Zhu, Wei Ren.
2022 American Control Conference (ACC), pp. 5081–5086, 2022.
```
@inproceedings{su2022optimization,
  title = {An optimization approach to fully distributed active joint localization and target tracking in multi-robot systems},
  author = {Su, Shaoshu and Zhu, Pengxiang and Ren, Wei},
  booktitle = {2022 American Control Conference (ACC)},
  pages = {5081--5086},
  year = {2022},
  organization = {IEEE},
  url = {https://ieeexplore.ieee.org/abstract/document/9867337}
}
```
```
Su, Shaoshu and Zhu, Pengxiang and Ren, Wei, "An optimization approach to fully distributed active joint localization and target tracking in multi-robot systems," 2022 American Control Conference (ACC), 2022.
```
Fully Distributed Active Joint Localization and Target Tracking Algorithms Design for Multi-Robot System.

Shaoshu Su.
University of California, Riverside, 2022
```
@book{su2022fully,
  title = {Fully Distributed Active Joint Localization and Target Tracking Algorithms Design for Multi-Robot System},
  author = {Su, Shaoshu},
  year = {2022},
  institution = {University of California, Riverside},
  url = {https://www.proquest.com/docview/2654401517?pq-origsite=gscholar&fromopenview=true&sourcetype=Dissertations%20&%20Theses}
}
```
```
Su, Shaoshu, "Fully Distributed Active Joint Localization and Target Tracking Algorithms Design for Multi-Robot System," , 2022.
```